performance-optimization
performance-optimization is a Backend performance & caching skill for AI agents, published by addyosmani in the agent-skills repository on GitHub. Skillspace rates performance-optimization D (66/100) and it passed the safety scan; a judge model has also reviewed it.
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 93,916
Placed #4 of 6 in the judged category final for Backend performance & caching.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #4 of 6 in the judged category final for Backend performance & caching.
- Trigger
85 85 - Instructions
88 88 - Specificity
85 85 - Safety
90 90 - Disclosure
42 42 - Maintenance
50 50
Excellent symptom-to-measurement decision tree spanning frontend and backend, but one dense file covering too much ground to stay lean.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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